2. Exploratory Plots [Map]

3.3 Map

Finally, we can make a map to see how the variables vary across US states

!pip install geopandas hvplot panel

import geopandas as gpd
import hvplot.pandas
import panel as pn

# Convert from wide to long data
us_rescaled_final_long = pd.melt(us_rescaled_final,
                                 id_vars = ['STATEFP', 'STATENS', 'GEOIDFQ', 'GEOID', 'STUSPS', 'NAME_x', 'LSAD','ALAND', 'AWATER', 'geometry', 'NAME_y', 'GEO_ID'],
                                 value_vars=['MedHHInc', 'EducTotal', 'EducBelowHighSch', 'EducHighSch', 'EducAssoc', 'EducBach', 'TotalPop', 'TotalPop16', 'LabForTotal', 'Unemployed', 'PopPovertyDetermined', 'PovertyPop', 'PctBach', 'PovertyRate', 'UnemploymentRate', 'LabForParticipationRate', 'netexport', 'REALGDP', 'life_expectancy', 'Labor_Productivity_2023', 'REALGDPpercapita']
                                 )

chart3 = us_rescaled_final_long.hvplot(
    c="value",
    dynamic=False,
    width=1000,
    height=1000,
    geo=True,
    cmap="viridis",
    groupby="variable")

chart3